code: def __init__(
      self,
      parent,
      do_resize: bool = True,
      size: Dict[str, int] = None,
      size_divisor: int = 32,
      do_rescale: bool = True,
      rescale_factor: Union[int, float] = 1 / 255,
      do_normalize: bool = True,
      do_center_crop: bool = True,
      image_mean: Optional[Union[float, List[float]]] = [
          0.48145466,
          0.4578275,
          0.40821073,
      ],
      image_std: Optional[Union[float, List[float]]] = [
          0.26862954,
          0.26130258,
          0.27577711,
      ],
      do_pad: bool = True,
      batch_size=7,
      min_resolution=30,
      max_resolution=400,
      num_channels=3,
  ):
      self.parent = parent
      self.do_resize = do_resize
      self.size = size if size is not None else {"shortest_edge": 288}
      self.size_divisor = size_divisor
      self.do_rescale = do_rescale
      self.rescale_factor = rescale_factor
      self.do_normalize = do_normalize
      self.do_center_crop = do_center_crop
      self.image_mean = image_mean
      self.image_std = image_std
      self.do_pad = do_pad
      self.batch_size = batch_size
      self.num_channels = num_channels
      self.min_resolution = min_resolution
      self.max_resolution = max_resolution
  
file_path: transformers/tests/models/bridgetower/test_image_processing_bridgetower.py
imports: import unittest
  from typing import Dict, List, Optional, Union
  from transformers.testing_utils import require_torch, require_vision
  from transformers.utils import is_vision_available
  from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
label_desc: Use image node_id 1 to create a new BridgeTowerImageProcessingTester object from inherited base classes: unittest with example: obj = BridgeTowerImageProcessingTester(parent, do_resize, size, size_divisor, do_rescale, rescale_factor, do_normalize, do_center_crop, image_mean, image_std, do_pad, batch_size, min_resolution, max_resolution, num_channels)